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Computer Vision with Embedded Machine Learning(으)로 돌아가기

Edge Impulse의 Computer Vision with Embedded Machine Learning 학습자 리뷰 및 피드백

63개의 평가

강좌 소개

Computer vision (CV) is a fascinating field of study that attempts to automate the process of assigning meaning to digital images or videos. In other words, we are helping computers see and understand the world around us! A number of machine learning (ML) algorithms and techniques can be used to accomplish CV tasks, and as ML becomes faster and more efficient, we can deploy these techniques to embedded systems. This course, offered by a partnership among Edge Impulse, OpenMV, Seeed Studio, and the TinyML Foundation, will give you an understanding of how deep learning with neural networks can be used to classify images and detect objects in images and videos. You will have the opportunity to deploy these machine learning models to embedded systems, which is known as embedded machine learning or TinyML. Familiarity with the Python programming language and basic ML concepts (such as neural networks, training, inference, and evaluation) is advised to understand some topics as well as complete the projects. Some math (reading plots, arithmetic, algebra) is also required for quizzes and projects. If you have not done so already, taking the "Introduction to Embedded Machine Learning" course is recommended. This course covers the concepts and vocabulary necessary to understand how convolutional neural networks (CNNs) operate, and it covers how to use them to classify images and detect objects. The hands-on projects will give you the opportunity to train your own CNNs and deploy them to a microcontroller and/or single board computer....

최상위 리뷰

필터링 기준:

Computer Vision with Embedded Machine Learning의 12개 리뷰 중 1~12

교육 기관: Michal L

2021년 9월 24일

교육 기관: Julian L

2021년 9월 24일

교육 기관: azadeh g

2022년 5월 27일

교육 기관: mauro g

2022년 2월 28일

교육 기관: Antonio R

2022년 9월 2일

교육 기관: Soren L

2022년 1월 9일

교육 기관: Latif U K

2022년 4월 3일

교육 기관: Akbar A

2022년 9월 8일

교육 기관: KAVITI R

2022년 9월 19일

교육 기관: Ralph Y

2021년 10월 24일

교육 기관: Irving A

2022년 3월 7일


2022년 8월 29일